It is requested to acquire data from each of monitoring cameras, microphones, and sensors connected via the Internet, to analyze or collate the acquired data, and to use the analyzed data or the collated data in business. For that purpose, it is desirable to acquire data and to store the acquired data in an available format.
On the other hand, in a case where data is acquired from all the sensors and an amount of data is enormously increased, there are cases where a large amount of data is stored in a recordable device such as a tape device. However, these devices are slow in reading speed and are not suitable for use.
It is preferable to compress a large amount of data and to store the compressed data in a hard disk or the like. For this reason, data compression techniques become important. In addition, since network traffic is increased, it is also important to reduce an amount of traffic by compressing data and transmitting the compressed data by a sensor device.
From such a viewpoint, a technique of performing lossless compression of multi-valued image data after rearranging bit strings such that a probability that the same bits sequentially appear becomes high, a technique of calculating a multi-stage transformation function based on components obtained by an inputted digital image signal and determining coefficients of the function so as to satisfy reversibility and to reduce output entropy, and the like are known.
Related techniques are disclosed in the following documents: Japanese Laid-open Patent Publication No. 2001-309185; Japanese Laid-open Patent Publication No. 2003-230139; David Salomon, “Data Compression”, ISBN: 978-0-387-40697-8; and Jean-Pierre Serre, “A Course in Arithmetic (Graduate Texts in Mathematics)”, Springer-Verlag New York, 1973.